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In light of the growing demand for green and low-carbon development, the advancement of low-carbon agriculture in alignment with China's specific national circumstances is imminent. Given this urgency, the accounting of non-CO2 greenhouse gas (GHG) emissions in China's agricultural system is still in the process of continuous research and improvement. Therefore, in this paper, we present an account of agricultural non-CO2 GHG emissions in Southwest China from 1995 to 2021, based on the carbon emission coefficient method. Furthermore, we explore the extent of the influence of the drivers and the relationship with economic development, utilizing the Stochastic Impact of Regression of Population, Affluence, and Technology (STIRPAT) model and the Tapio model. We observe a general trend of increasing and then decreasing non-CO2 GHG emissions from agriculture in the Southwest region, with a pattern of higher in the center and lower in the east and west. Economic, demographic, structural, and technological levels show different degrees of impact in different provinces, favoring the development of targeted agricultural planning policies in each region. For the majority of the study period, there was a weak or strong decoupling between economic growth and GHG emissions. Finally, recommendations are made to promote low-carbon agricultural development in Southwest China, providing a database and policy support to clarify the GHG contribution of the agricultural system. [ABSTRACT FROM AUTHOR]

Agricultural mulching is an important input for modern agricultural production and plays an important role in guaranteeing food security worldwide. At present, polyethylene (PE) mulching is still commonly used in agricultural production in most countries around the world, which is non-biodegradable, and years of mulching have caused serious agricultural white pollution. Lignin is one of the three major components of plant cell walls, and it is also the main renewable natural aromatic compounds in nature. Lignin-based composite film materials are green, biodegradable, and show good prospects for development in the field of agricultural mulch. This paper introduces the types, structure, and application status of lignin, summarizes the preparation of lignin-based composite film materials and its latest research progress, focuses on the types, preparation methods, and application examples of lignin-based agricultural mulching, and looks forward to the future development prospects of lignin-based agricultural mulching. [ABSTRACT FROM AUTHOR]

Population growth, coupled with industrial and agricultural development, has resulted in increased demand for freshwater supply. For countries with scarce water resources, desalination constitutes the only viable solution to this problem. Reverse osmosis (RO) technology has become widely used as the membrane materials have been upgraded and the costs have been reduced. Nowadays, RO is the foremost technology for desalting different types of water such as seawater, brackish, and tap water. However, its design is critical since many parameters are involved in obtaining a good design. The high use of RO encourages the establishment of a procedure that facilitates the design process and helps in obtaining an optimum-performance RO desalination system. This paper presents a procedure divided into three parts: (1) classifying RO parameters; (2) choosing the parameters in a certain order and doing the calculation process through 12 steps; and (3) then inserting the selected parameters and the obtained values on RO System Analysis (ROSA) software. These points are then summarized by creating an algorithmic chart to follow during the design phase of the RO system using ROSA. An example on the proposed list is then taken to validate the procedure, and a comparison is conducted on choosing different values for the parameters. The results of this comparative study show that choosing different parameters affects the RO system productivity. Additionally, every design has a specific optimum set of parameters, which depends upon the design constraints set by the user. [ABSTRACT FROM AUTHOR]

It is very important to enhance the risk resistance of the agricultural sector to realize the modernization transformation of the agricultural industry and strengthen the competitiveness of national agriculture. Based on the relevant spatial data of 30 provincial administrative regions in China from 2013 to 2022, this study constructs a multi-dimensional index framework to comprehensively evaluate the resilience of China's agricultural economy by comprehensively considering the three key aspects of adaptability, management strategy, and innovation drive. This study adopts several quantitative analysis tools including the Theil index, global and local analysis of the Moran I index, and kernel density estimation (KDE), and further combines with the spatial Durbin model (SDM) to conduct an in-depth spatiotemporal analysis of the resilience of China's agricultural economy. This study not only reveals the evolution trend of agricultural economic resilience in different times and spaces but also analyzes the differences in resilience among regions and its spread in space. Through these refined analytical tools, we aim to reveal how agricultural economic resilience changes over time, the differences in resilience levels among regions, and the geospatial interactions and diffusion. This study reveals a series of key findings: (1) The resilience of China's agricultural economy shows a trend of steady improvement. (2) Differences within the three regions are the main factors generating differences in the development of resilience in China's agricultural economy. (3) The resilience of the agricultural economy in different regions shows obvious spatial correlations. (4) Further analysis shows that the efficiency of agricultural production and the urbanization process have a positive direct impact on the resilience of the agricultural economy, and this impact has a significant positive spatial diffusion effect. Meanwhile, although the level of agricultural mechanization is not significant in its direct impact, it has a positive spatial impact on the enhancement of agricultural economic resilience in other regions. In addition, the restructuring of agricultural cropping has both direct negative impacts and positive spatial spillover effects on the resilience of the agricultural economy. Based on these findings, this paper suggests that agricultural policies should consider regional development differences, implement differentiated agricultural support policies, fully account for the spatial spillover effects of agricultural ecological efficiency, and strengthen the exchange and cooperation of resources between regions. This study deepens the understanding of the spatial and temporal characteristics of the resilience of China's agricultural economy, reveals its inherent dynamic processes and spatial interactions, and provides valuable references for policymakers and practitioners to better cope with the various challenges encountered in agricultural production, and to jointly promote the sound development of China's agricultural economy. [ABSTRACT FROM AUTHOR]

The advancement of agricultural technology has increasingly positioned robotic detection and localization techniques at the forefront, ensuring critical support for agricultural development through their accuracy and reliability. This paper provides an in-depth analysis of various methods used in detection and localization, including UWB, deep learning, SLAM, and multi-sensor fusion. In the domain of detection, the application of deep algorithms in assessing crop maturity and pest analysis is discussed. For localization, the accuracy of different methods in target positioning is examined. Additionally, the integration of convolutional neural networks and multi-sensor fusion with deep algorithms in agriculture is reviewed. The current methodologies effectively mitigate environmental interference, significantly enhancing the accuracy and reliability of agricultural robots. This study offers directional insights into the development of robotic detection and localization in agriculture, clarifying the future trajectory of this field and promoting the advancement of related technologies. [ABSTRACT FROM AUTHOR]

Introduction: China’s rural financial landscape has long been characterized by exclusion, leaving countless farmers without access to essential financial services. However, the advent of digital financial inclusion presents a promising solution, offering low-cost, high-penetration avenues to bolster agricultural sustainability. This paper unravels how “Byte-Sized Finance” can yield “Bushel-Sized Benefits” in China’s agricultural green development. Methods: Methodologically, we pioneer a novel system to gauge agricultural green development across 31 Chinese provinces spanning from 2013 to 2021. Empirically, employing fixed-effect, mediation effect, and spatial Durbin models. Results: Our study reveals the intricate pathways through which digital financial inclusion influences agricultural green development. We find that it exerts its impact through the lenses of industrial structure and entrepreneurship, operating at both macro and micro levels. Furthermore, our analysis uncovers spatial spillover effects, shedding light on the differential roles played by these mechanisms across regions. Discussion: This groundbreaking discovery underscores the transformative potential of leveraging digital financial inclusion to propel China toward agricultural green development. By shedding light on these crucial dynamics, our findings offer insights for policymakers, researchers, and practitioners striving to foster sustainability within China’s agricultural sector. [ABSTRACT FROM AUTHOR]

A new video based multi behavior dataset for cows, CBVD-5, is introduced in this paper. The dataset includes five cow behaviors: standing, lying down, foraging,rumination and drinking. The dataset comprises 107 cows from the entire barn, maintaining an 80% stocking density. Monitoring occurred over 96 h for these 20-month-old cows, considering varying light conditions and nighttime data to ensure standardization and inclusivity.The dataset consists of ranch monitoring footage collected by seven cameras, including 687 video segment samples and 206,100 image samples, covering five daily behaviors of cows. The data collection process entailed the deployment of cameras, hard drives, software, and servers for storage. Data annotation was conducted using the VIA web tool, leveraging the video expertise of pertinent professionals. The annotation coordinates and category labels of each individual cow in the image, as well as the generated configuration file, are also saved in the dataset. With this dataset,we propose a slowfast cow multi behavior recognition model based on video sequences as the baseline evaluation model. The experimental results show that the model can effectively learn corresponding category labels from the behavior type data of the dataset, with an error rate of 21.28% on the test set. In addition to cow behavior recognition, the dataset can also be used for cow target detection, and so on.The CBVD-5 dataset significantly influences dairy cow behavior recognition, advancing research, enriching data resources, standardizing datasets, enhancing dairy cow health and welfare monitoring, and fostering agricultural intelligence development. Additionally, it serves educational and training needs, supporting research and practical applications in related fields. The dataset will be made freely available to researchers world-wide. [ABSTRACT FROM AUTHOR]

Momilactones are defined as every lactone derived from rice husk. To date, these compounds can only be naturally found in rice (Oryza lineage) and moss (Pseudoleskeella papillosa and Hypnum plumaeforme). Their basic structure refers to the (9β-H)-pimarane skeleton bearing a γ-butyrolactone. In this review, the beneficial properties of momilactones, especially momilactones A (MA) and B (MB), including allelopathy, antimicrobials, antioxidants, anti-chronic diseases, anti-inflammation, and anticancer, are highlighted. Additionally, the signaling roles of momilactones in the response of host plants against environmental stresses are discussed, raising the question of whether momilactones act as novel phytohormones that require further comprehensive clarification. In another aspect, we come up with promising approaches to the future exploitation of these valuable compounds based on the current knowledge of their bioactivity mechanisms, biosynthetic pathways, and isolation protocols. However, momilactone biosynthetic processes remain elusive. Moreover, challenges in researching these compounds are mainly due to difficulties in isolation procedures and the lack of commercial sources, which have been least improved over the last half-century. Accordingly, we propose promising strategies to address these present problems and promote the effectiveness of further research, including: i) to improve the efficiency of momilactone extraction and isolation from plant sources; ii) to increase momilactone production applying synthetic models; iii) to generate crops that accumulate greater momilactone contents through genetic engineering approaches; iv) to discover new applications that combine momilactones with other prospective substances for enhancing targeted biological properties and preventing undesirable impacts; and v) to employ smart farming for optimizing the application of momilactones, monitoring their levels, and promoting sustainable agriculture. This paper may provide valuable insights for future strategies, focusing on the exploitation of momilactones for human health-beneficial purposes and the development of green agriculture aligned with sustainable development targets. [ABSTRACT FROM AUTHOR]

Soil salinization seriously restricts the development of agricultural production, the sustainable use of land resources, and the stability of the ecological environment. In order to objectively reveal the research status of soil salinization, CiteSpace software was used to conduct data mining and quantitative analysis on research papers on soil salinization from 2008 to 2023 in China National Knowledge Infrastructure (CNKI) and Web of science databases. The data sources were transformed into visual graphs by reproducing clustering statistics from aspects such as publication volume, authors, keywords, and publishing institutions. In addition, this paper also combined the actual needs and cutting-edge hotspots in relevant research in China, and proposed and analyzed the limitations and future development trends of soil salinity monitoring research in China. This has important practical significance for comprehensively grasping the current research status of salinization, further clarifying and sorting out the research ideas of salinization monitoring, enriching the remote sensing monitoring methods of saline soil, and solving the actual problems of soil salinization in China. [ABSTRACT FROM AUTHOR]

In China's rural land system, the collective owns the land, and farmers, as members of the collective, can acquire land contractual management rights through land contracting. With the second round of land contracts nearing expiration, the central government has announced that the term should be extended for 30 years. This paper introduces the theory of psychological ownership to explore the implementation paths of the 30-year extension policy. The study finds that (1) farmers generally exhibit strong psychological ownership towards the contracted land. (2) The Household Contract Responsibility System satisfies the three routes for the formation of psychological ownership—control, intimate knowledge, and self-investment. As the duration of farmers' possession of contracted land extends, their psychological ownership gradually forms and strengthens. (3) Farmers' psychological ownership has both positive and negative effects. The 30-year extension policy must adhere to the path dependence formed by the evolution of the land contract system, comply with the institutional constraints imposed by rural land collective ownership, and simultaneously meet the practical demands posed by urban–rural integration and agricultural development. Drawing on the complex effects of farmers' psychological ownership and considering the historical, institutional, and practical contexts of policy implementation, this study proposes the dual necessity of facilitating and restraining farmers' psychological ownership when extending for another 30 years and offers corresponding policy suggestions. Facilitation requires empowering farmers with more stable land possession and stronger land rights. Restraint requires preventing the permanent locking of rural land allocation patterns to achieve fair and efficient land allocation. [ABSTRACT FROM AUTHOR]

With the development of agricultural production, the demand for electricity correspondingly increases. To sustainably meet this demand, renewable energy sources (RESs) can be utilized. This paper explores the application of RES alternatives in agriculture to provide guidelines for enhancing sustainable agricultural practices in Bosnia and Herzegovina. The study employs expert decision making using fuzzy multi-criteria decision-making (MCDM) methods. A decision-making model incorporating nine criteria and six alternatives was developed. Using the direct weight calculation (DiWeC) approach, the findings indicate that economic criteria are prioritized over other sustainability criteria. The results from the fuzzy RAWEC (ranking of alternatives with weights of criteria) method reveal that solar energy has the greatest potential for advancing sustainable agricultural production in Bosnia and Herzegovina. For practical implementation of RES alternatives, active involvement from state institutions and local communities is essential. [ABSTRACT FROM AUTHOR]

Alluvial fans have been proven to have great utilisation potential in QTP, but to what extent they are suitable for agricultural development is unknown. Therefore, using the alluvial fan in the Lhasa River Basin (LRB) as a case study, this paper established an evaluation system of land suitability for agriculture (LSA). Principal component analysis (PCA) and the exhaustive method (EM) were used to define the minimum dataset (MDS) and then the LSA of the alluvial fan in the LRB was evaluated using a comprehensive index of LSA. Two scientific approaches were implemented to improve the LSA using a scenario simulation. The results showed that the MDS assessed by the EA was more representative compared to the PCA. Alluvial fans with suitable grades are mainly distributed in the Lhasa River's middle and lower reaches. Developing facility agriculture and repairing roads accessing the alluvial fans are effective approaches to improve the LSA, which can increase the suitable-grade area from 58.62% to 97.82% and 63.85%, respectively. Therefore, most alluvial fans in the LRB are suitable for developing agriculture, and under the influence of human activities, there will be more alluvial fans suitable for developing agriculture. Our research provides scientific methods for the sustainable development of land in alpine regions. [ABSTRACT FROM AUTHOR]

Scientific and accurate estimation of rice yield is of great significance to food security protection and agricultural economic development. Due to the weak penetration of high frequency microwave band, most of the backscattering comes from the rice canopy, and the backscattering coefficient is highly correlated with panicle weight, which provides a basis for inversion of wet biomass of rice ear. To solve the problem of rice yield estimation at the field scale, based on the traditional water cloud model, a modified water-cloud model based on panicle layer and the radar data with Ku band was constructed to estimate rice yield at panicle stage. The wet weight of rice ear scattering model and grain number per rice ear scattering model were constructed at field scale for rice yield estimation. In this paper, the functional area of grain production in Xiashe Village, Xin'an Town, Deqing County, Zhejiang Province, China was taken as the study area. For the first time, the MiniSAR radar system carried by DJI M600 UAV was used in September 2019 to obtain the SAR data with Ku band under polarization HH of the study area as the data source. Then the rice yield was estimated by using the newly constructed modified water-cloud model based on panicle layer. The field investigation was carried out simultaneously for verification. The study results show: the accuracies of the inversion results of wet weight of rice ear scattering model and grain number per rice ear scattering model in parcel B were 95.03% and 94.15%; and the accuracies of wet weight of rice ear scattering model and grain number per rice ear scattering model in parcel C+D+E were over 91.8%. In addition, different growth stages had effects on yield estimation accuracy. For rice at fully mature, the yield estimation accuracies of wet weight of ear and grain number per ear were basically similar, both exceeding 94%. For rice at grouting stage, the yield estimation accuracy of wet weight of ear was 92.7%, better than that of grain number per ear. It was proved that it can effectively estimate rice yield using the modified water-cloud model based on panicle layer constructed in this paper at panicle stage at field scale. [ABSTRACT FROM AUTHOR]

In order to study the impact of inclusive finance on agricultural green development, This paper uses both static panel and dynamic panel (system GMM model) estimation methods to make empirical analysis of the impact of inclusive financial development on agricultural green development. The results both find that there is a significant positive correlation between the level of inclusive financial development, real GDP per capita, the proportion of the added value of agriculture, forestry, animal husbandry and fishery in GDP and agricultural green development. This paper puts forward some countermeasures and suggestions to promote agricultural green development, including vigorously developing inclusive finance, promoting economic growth, promoting the development of agriculture, forestry, animal husbandry and fishery, and increasing environmental protection expenditures. [ABSTRACT FROM AUTHOR]

With the development of the market economy, agricultural trade has become more and more significant for the development of the agricultural economy, which has triggered people's further thinking and exploration on the impact of agricultural trade on agricultural carbon emissions. This paper takes the measurement of trade implied carbon as the carbon dioxide emission index under the impact of agricultural trade and analyzes the impact of trade implied carbon and implied carbon balance on carbon emission. Taking the impact of Sino-US agricultural trade as an empirical background, this paper measures the impact of environmental changes in agricultural trade opening on China's agricultural development and its carbon emissions, so as to predict changes in China's regional agricultural carbon emissions performance. After calculation, it is found that the scale of China's exports has decreased by 0.089%, which is lower than the decline of 0.361% in the United States. The trade conflict has a significant impact on China's import and export structure. Under the scenario of mutual tariffs on agricultural products, China's exports to the United States are expected to decrease by 6.28%, while China's imports from the United States decreased by 13.02%. The Sino-US agricultural trade dispute will reduce China's carbon emissions by 0.013% and the United States' carbon emissions by 0.024%, which is related to the negative impact on the economy. Improving the performance of agricultural carbon emissions is not only the need for the green and sustainable development of the agricultural economy but also conducive to improving the international competitiveness of agricultural products. [ABSTRACT FROM AUTHOR]

Accurately identifying the matching relationships between territorial space evolution and the resources and environment carrying capacity will directly guide the sustainable use of territorial space. Based on the evaluation of the territorial space dynamics of the lower Yellow River, this paper evaluates the suitability of territorial space development by focusing on ecological protection, agricultural development, and urban construction. Specifically, the resources and environment carrying capacity is estimated by identifying and mediating potential conflicts in the development of territorial space. The matching relationship between the evolution of territorial space and the resources and environment carrying capacity is identified using the matching degree model. The results demonstrated that: (1) Between 2000 and 2020, the agricultural space of the lower Yellow River was relatively stable, while the ecological space was generally shrinking, and the urban space continued to increase; (2) The characteristics of suitability for the agricultural development and urban construction of the lower Yellow River are characterized by landform and land-sea differentiation. The carrying scale of resources and the environment is based on agricultural space and is increasing yearly, followed by ecological space, which is gradually decreasing, and urban space, which first increased and then decreased; (3) Between 2000 and 2020, the matching index of the ecological and agricultural space evolution and the resource and environmental carrying capacity in the lower Yellow River exhibited a downward trend, while the regional difference increased. Furthermore, the matching index of urban space and the resources and environment carrying capacity indicated an upward trend, while the regional difference decreased. [ABSTRACT FROM AUTHOR]

Purpose: Intellectual property right constitutes play a forceful role to promote economic growth and create a fortune. However, it is not yet clear to what extent the agricultural intellectual property rights represented by geographical indications of agricultural products (AGIs) can affect the development of regional economy. The purpose of this paper is to analyze this impact and its mechanism as well as to draw policy implications from this empirical analysis. Design/methodology/approach: Using county-level panel data from 2006 to 2020, this paper employed the difference-in-differences (DID) model. Findings: The authors find that AGIs can significantly improve economic development at the county level. The AGIs can stimulate the flow of commercial and industrial capital to the countryside, thus fueling county-level economic development. Unlike AGIs for cereals and cash crops, AGIs for aquatic products and animal products cannot influence or have a negative impact on county-level economic. Compared with Eastern regions, the acquisition of AGIs in Western regions can more significantly boost county-level economic development. Therefore, AGIs can pronouncedly narrow down the gap of cross-county economic growth. Originality/value: Conclusions of this paper can provide references for building the county-level countryside into a main ground of agricultural economic development and brand construction, continuously promoting the agricultural supply-front structural reform and boosting realization of all-around rural revitalization. [ABSTRACT FROM AUTHOR]

This paper examines the contributions of public-Private partnership in Agriculture to grassroots development with emphasis on Shonga Farms' experience. The curiosity to conduct the study was predicated on the need to determine the viability of commercializing agriculture in developing country like Nigeria. The main objectives of the study are to evaluate the contributions of Shonga Farms to rural development in food supply, income generation, infrastructural development and employment generation in Shonga communities of Kwara State. In efforts toward achieving the above objectives, stakeholder's theory was adopted as a theoretical underpinning for the paper. Methodologically, the paper adopted a survey research design for data collection. Out of 204 questionnaire administered to selected respondents, 183 were completed and returned properly. Subsequently, descriptive statistics and Analysis of Variance (ANOVA) were adopted for the analysis of research questions and test of hypotheses. The findings of the study reveal that Shonga Farm has significantly increased the capacity of employment generation, food production, income generation and infrastructural development in Shonga community. However, the inability to complete Kanji Dam irrigation project made it difficult for the company to farm during the dry seasons. Overall, the study recommended for a reduction in the high rate of tariff on imported farm equipment and inputs in order to enable Shonga Farms procure high quality inputs such as: seeds, fertilizers, herbicides and machineries. The Central Bank of Nigeria and Nigeria Agricultural Cooperative and Rural Development Bank should come to the aid of Shonga Farm by ensuring speedy completion of Kanji Dam irrigation project to encourage all round farming throughout the year. [ABSTRACT FROM AUTHOR]

The present study examines the research on agriculture 4.0 from 1965 to 2022. The bibliometric approach was adopted to analyse the current research trends in Agriculture 4.0. MS Excel, R software (Biblioshiny) was utilised to analyse and visualise the data. The present study will analyse the literature's publication pattern and growth rate in Agriculture 4.0. During this period, 1869 documents were published by 7,258 authors, and 1040 sources were considered for the study. The publication pattern was analysed using different bibliometric aspects like chronological contribution of papers, year-wise growth of publication, geographical distribution of papers, authorship pattern, author productivity, etc., which provide in-depth information about the publication pattern of Agriculture 4.0. The development of Agriculture 4.0 has grown rapidly over the last decade, and despite the growing interest in it, studies are still needed to develop its theory. Agriculture 4.0 is an emerging new technology that is like a revolution in agriculture; by adopting the concept, agricultural scientists can reach a proper conclusion in the literature. It is necessary to make Agriculture 4.0 more understandable and accessible to farmers. This exciting field has led to new discoveries and expansions in agriculture. For the successful use of Agriculture 4.0, it will be necessary to make progress at all levels of crops, from specialty crops to traditional crops. [ABSTRACT FROM AUTHOR]

The coupling coordination of agricultural technology innovation with food security is of great significance for high-quality agricultural development. By identifying the coupling coordination relationship between the two systems and the influencing factors, this paper aims to promote the virtuous cycle of coordinated development between regional agriculture and technology, as well as accelerate the realisation of high-quality development of Chinese agriculture. Therefore, this paper explores the spatial and temporal coupling characteristics of the two using the entropy value method, coupling coordination degree model, and exploratory spatial data analysis, and it screens for important influencing factors using the grey correlation model. The main results show that ① the coupling coordination relationship between agricultural technology innovation and food security in China is at a dissonant stage, but the value of the coupling coordination degree increases from 0.2076 to 0.3437 during the period of study, and the level of coordination gradually improves. ② The degree of coupling coordination in the provincial space exhibits a distribution pattern of "high in the east and low in the west". The areas of high value are primarily situated in the provinces of Shandong, Jiangsu, and other provinces along the southeastern coast of China, while the areas of low value are mainly located in the provinces of Qinghai, Ningxia, and other provinces in inland northwest China. ③ The Moran's index of provincial coupling coordination is greater than 0, showing a certain positive correlation, and there is a significant pattern of spatial aggregation. ④ The correlation coefficients between the influencing factors and the degree of coupling coordination are all greater than 0.35, indicating a moderate or high correlation, but the significance of technological support capacity and food distribution security increased over time. [ABSTRACT FROM AUTHOR]

This theoretical research article examines the transformative potential of artificial intelligence (AI) in revolutionising agricultural practices within India's rural and industrial sectors. With the dual objectives of enhancing agricultural productivity and fostering sustainable development, the study synthesises existing literature on AI applications such as precision agriculture, crop health monitoring through drones and AI-based pest management systems. It highlights the significant disparities in technology adoption between urban and rural areas and proposes an integrative framework to bridge these gaps. The paper proposes a model that leverages AI to optimise resource allocation, predict crop yields with greater accuracy and reduce wastage, thus contributing to economic stability and increased profitability for farmers. Additionally, the paper explores the socioeconomic impacts of AI-driven innovations, including potential job displacement due to automation and the requisite strategies for skill development and retraining in rural communities. By analysing case studies and pilot projects currently underway in India, this research forecasts the challenges and opportunities of AI integration in rural agricultural practices. The findings suggest that while AI offers considerable benefits in terms of efficiency and output, its successful implementation requires robust infrastructure, continuous education and policy support tailored to the unique needs of rural India. In conclusion, the article calls for a multi-stakeholder approach involving government, industry leaders and academic institutions to establish a sustainable ecosystem for AI adoption in agriculture. It emphasises the need for policies that prioritise equitable access to technology and foster an inclusive growth environment. This study lays the groundwork for future empirical research and the development of targeted AI tools that cater specifically to the nuances of the Indian rural agricultural sector. [ABSTRACT FROM AUTHOR]

The use of agricultural films, pesticides, and fertilizers has increased in China, leading to the degradation of the agricultural ecological environment. Based on the panel data of 30 provinces in China from 2010 to 2021, this paper takes agricultural film usage as the threshold variable to study the impact of pesticide and fertilizer usage on agricultural development. The research results show that a single threshold effect of agricultural film usage is significant. When agricultural film usage is both a core and threshold variable, that is lower than the threshold value, every 1% increase in agricultural film usage will reduce agricultural output value by 0.9862%, and the impact is significant. When agricultural film usage crosses the threshold value, every 1% increase in agricultural film usage will increase agricultural output value by 1.1843%, and the impact is significant. When pesticide usage is the core variable, regardless of whether agricultural film usage is below or above the threshold, pesticide usage promotes agricultural development. Its impact is significant. When fertilizer input is a core variable, regardless of whether agricultural film usage is below or above the threshold, the use of fertilizers hinders agricultural development. The impact of fertilizer input on agricultural development is significant. Through empirical testing, this paper explores the deep relationship between agricultural film usage, pesticide usage and fertilizer input on agricultural development. These can effectively allocate agricultural production factors, transform the mode of agricultural economic growth, achieve the coordinated development of the ecological environment and agricultural economy and provide data support for the formulation of agricultural green development policies. [ABSTRACT FROM AUTHOR]

Digital technologies represent a new direction increasing the efficiency of the agro-industrial sector and the sustainable development of agriculture. At the current stage, we can note the role of the transmissibility of new technologies and innovations in the agri-food complex, vis-a-vis regional improvement and development, the need for economic-financial and human sources for the implementation of innovations, as well as the efficiency of their implementation in practice. Management efficiency is treated through the complex and synergistic approach of economic, financial and ecological efficiency of enterprises. The purpose of the present article is to propose the digital assurance chain and to analyze the importance of current digital services in the development of intelligent management in agriculture. In the process of developing the objectives proposed in this article, the authors used the following methods, such as: analysis and synthesis, the statistical and mathematical method, the comparative method, the survey, the interview that would ensure the development of the entire economy by ensuring the sustainability of the agri-food sector. The proposed proposals will be used by agricultural entrepreneurs, not taking into account specialization and fields of activity, as well as by certain state institutions in the Republic of Moldova. [ABSTRACT FROM AUTHOR]

The formation of the scientific and intellectual potential of the agri-food complex contributes to the achievement of sustainable socio-economic growth. The article proposes models for the development of the scientific and intellectual potential of the Russian agri-food complex. An analysis of the activities of existing institutes for the development of agricultural scientific research was carried out. The assessment of the state of scientific and intellectual potential was carried out on the basis of cross-country comparisons of indicators of the number of researchers and expenditures on research and development. Empirically, imbalances were identified between the number of researchers and internal R&D costs. The positive experience of forming the scientific and intellectual potential of countries with developed market economies has been systematized, priority directions and stimulation of innovation and investment development have been identified. The practical significance of the research results lies in increasing the efficiency of agricultural production based on the development of scientific and intellectual potential. [ABSTRACT FROM AUTHOR]

State aid to certain economic sectors in the European Union was an acceptable model until the establishment of the single market in 1992. The EC acknowledge that the allowance is imputable to the MS and that it constitutes State aid. In the light of the foregoing, the Commission concludes that the measures at issue in the present case constitute State aid (Article 107(1) TFEU). "Special rules on provision of state aids were created as secondary law rules by the EU Council and EU Commission". State aid to promote the economic development of the agricultural sector is part of the wider framework of the "Common Agricultural Policy" ("CAP"). This paper analyzes EU state aid regulation in the agriculture sector, with special focus on the provisions of the "Agriculture Block Exemption Regulation" -- ABER. The paper also analyzes agricultural aid, which must be notified to the EC as being authorized under the "Agriculture Guidelines". [ABSTRACT FROM AUTHOR]

The development of agricultural robots is an increasingly popular research field aiming at addressing the widespread labor shortages in the farming industry and the ever-increasing food production demands. In many cases, multiple cooperating robots can be deployed in order to reduce task duration, perform an operation not possible with a single robot, or perform an operation more effectively. Building on previous results, this application paper deals with a cooperation strategy that allows two heterogeneous robots to cooperatively carry out grape harvesting, and its implementation is demonstrated. More specifically, the cooperative grape harvesting task involves two heterogeneous robots, where one robot (i.e., the expert) is assigned the grape harvesting task, whereas the second robot (i.e., the helper) is tasked with supporting the harvesting task by carrying the harvested grapes. The proposed cooperative harvesting methodology ensures safe and effective interactions between the robots. Field experiments have been conducted in order firstly to validate the effectiveness of the coordinated navigation algorithm and secondly to demonstrate the proposed cooperative harvesting method. The paper reports on the conclusions drawn from the field experiments, and recommendations for future enhancements are made. The potential of sophisticated as well as explainable decision-making based on logic for enhancing the cooperation of autonomous robots in agricultural applications is discussed in the context of mathematical lattice theory. [ABSTRACT FROM AUTHOR]

Despite their substantial economies and populations, South Africa and Nigeria encounter significant challenges primarily due to constraints in accessing to agricultural input resources. The study adopts an interpretivist approach, which involves acknowledging reality and making meaningful contributions through qualitative research. As such, secondary data was collected and analysed thematically. This paper delves into the multifaceted nature of food insecurity, highlighted by historical factors, widespread poverty and unemployment, further exacerbated by escalating global food prices. The correlation between exorbitant input expenses and restricted agricultural yields and production, resulting in heightened food prices, is thoroughly explored. Additionally, the review critically examines the influence of climate change on the agricultural sector and its implications for the availability and accessibility of food in rural areas. The narrative in this paper emphasises the imperative of fairness, equity, transparency, and accountability in formulating sustainable strategies to combat these challenges. The paper advocates for contextually appropriate, evidence-based policy approaches, emphasising the significance of collaborations between research institutions and government entities. Such partnerships are crucial for developing efficacious responses to issues like drought, which necessitate comprehensive monitoring systems and mitigation strategies. The role of local government in fostering the growth of agro-based enterprises is underscored, illustrating how local processing of agricultural products can augment revenue, employment, and overall agricultural productivity. The paper also proposes policies to attract private sector investment, such as subsidies for farming equipment and fertilisers, and the development of climate-resilient agricultural technologies that integrate local indigenous knowledge. Lastly, the paper addresses the critical imperative of enhancing the resilience of supply chains against unforeseen disruptions, encompassing natural disasters and market fluctuations. This entails implementing risk management strategies, investing in infrastructure, adopting advanced technologies, and fostering collaboration throughout the supply chain. The paper concludes that such measures are indispensable for ensuring a stable and consistent supply of agricultural products, ultimately benefiting both producers and consumers and contributing to the overarching goal of attaining food security in South Africa, Nigeria, and similar contexts. [ABSTRACT FROM AUTHOR]

The article focuses on assessing the impact of China's agricultural machinery purchase subsidy policy on polluting agricultural production behaviors, utilizing quasi-natural experimental characteristics and the difference-in-differences approach. Topics include a significant improvement in agricultural mechanization, varied effects on pollution behaviors such as reduced plastic film use and increased straw-burning, and changes in farmers' practices affecting ecological environments.

In the early 1980s, to control soil and water loss in the rainy season and problems of water shortages in the dry season in the red soil hilly region of central Jiangxi, the academician team of Li Wenhua from Qianyanzhou Station of the Chinese Academy of Sciences proposed a comprehensive muti-dimensional agriculture development mode known as the "Qianyanzhou Mode". Since then, models for the forest-livestock-food ecosystem, forest-fruit-economy ecosystem, and land-water compound muti-dimensional system and others have been tested, demonstrated, promoted and used to solve major issues in ecological restoration and agricultural production. With the dawn of the new era, the Qianyanzhou Mode is being given new connotations. In order to reduce the use of pesticides and eliminate the use of antibiotics for improving the quality of agricultural products, increasing farmers' income, and assisting in strategies for rural vitalization, Qianyanzhou Station is currently focusing on the development of experiments and demonstrations of green agricultural development modes, such as forest-fruit-fowl, hybrid paper mulberry-pig-fruit, grass-sheep(cattle)-fertilizer-fruit, hybrid paper mulberry-fish-goose, paddy-shrimp, and others. The goal of this new effort is to apply the wisdom of Qianyanzhou to the construction of the ecological civilization, including ecological environment protection and the prosperity of farmers in the old revolutionary base areas in central Jiangxi Province. [ABSTRACT FROM AUTHOR]

Purpose: In this paper, the heterogeneity of the linkages among financial development, productivity and growth across income groups is emphasized. Design/methodology/approach: An empirical analysis is conducted with an illustrative sample of 130 economies over the period 1991–2019 and classified into four subsamples: Organisation for Economic Co-operation and Development (OECD), developing, least developed and net food importing developing countries. Forecast error variance decompositions and panel vector auto-regressive estimations are computed, with insightful findings. Findings: Higher levels of output stimulate the economic development in the agricultural sector, mainly via the productivity channel and, in the most developed economies, also through access to credit. Differently, in developing and least developed economies, the role of access to credit is marginal. The findings have practical implications for stakeholders involved in the planning of long-run investments. In less developed economies, priorities should be given to investments in technology and innovation, whereas financial markets are more suited to boost the development of the agricultural sector of developed economies. Originality/value: The authors conclude on the credit–output–productivity nexus and contribute to the literature in (at least) three ways. First, they assess how credit access, agricultural output and agricultural productivity are jointly determined. Second, they use a novel approach, which departs from most of the case studies based on single-country data. Third, they conclude on potential causality links to conclude on policy implications. [ABSTRACT FROM AUTHOR]

In Moldova, the adoption of the Law for Ecological Agri-Food Products (2005) and the Law on Subsidizing Principles in Agriculture and Rural Development (2016) contributed to the beginning of government support for organic farming. The objective of this paper is to examine the influence and effectiveness of support policies for the growth of organic farming. The legal documents for the programs and policies adopted are the framework for the data analysis. Secondary data from the Agency of Interventions and Payments in Agriculture (AIPA) regarding the number of applications, converted area, and analysis of allocated subsidies for organic agricultural development were used for the impact analysis. Due to differences between national legislation and European policies, local ecological certificates are not recognized on the E.U. market, which creates challenges for export under the organic label. This is a major issue for the development of organic farming in Moldova. The lack of control capacity of conversions, certification of technologies, raw materials and organic products, and few professional trained workers in organic agriculture cause additional problems to farmers restricting the expansion of ecological agriculture in Moldova. [ABSTRACT FROM AUTHOR]

Agricultural and rural development is a very current issue in the world. Today, agriculture is expected to meet the growing demands for the production of a sufficient amount of food. So, it is necessary to increase productivity in agriculture, while taking into account the longterm agricultural sustainability. The implementation of digitalization in agriculture leads to increased productivity, enables the growth of agricultural producers' profits and maintenance of food security. The aim of the paper is to analyze the application of digitalization in agriculture on farms in AP Vojvodina. In the paper 46 farms from the territory of AP Vojvodina were surveyed as part of the research. The results of the research showed that digital technology is still not used enough on farms in AP Vojvodina, and the main limiting factors are financial resources, education and lack of different types of training. [ABSTRACT FROM AUTHOR]

Nowadays, frequent climate extremes exert a serious impact on agricultural production and social development, which is seldom studied in the previous literature. Production–Living–Ecological (PLE) is a useful analysis framework, and China is a suitable model for such study. This paper takes the Huai River Eco-Economic Belt (HREB), an important agricultural zone in China, to study the relationship among agricultural production (P), society (L), and climate change (E), which is referred to as APLE. This paper constructs a coupled coordination evaluation index system for the APLE system and uses coupling coordination degree models and geographic detector to study the spatial and temporal evolution of the coordinated development of 34 counties (cities) in the HREB from 2009 to 2018. The results show the following: (1) The development of the agricultural subsystem and the social subsystem formed a "scissors difference" from 2009 to 2014, and the three subsystems showed a slight upward trend during 2014–2018. (2) The coupling and coordinated development of the APLE system in the HREB was generally stable, and the coupling coordination degree was improved from low-grade and slightly uncoordinated to barely and primarily coordinated. Furthermore, the spatial differentiation of the coupling coordination degree shows a clear pattern of being high in the southeast and low in the northwest. (3) The main influencing factors are the drought and flood protection rate, the effective irrigation rate, the per capita electricity consumption in agriculture, the number of beds in healthcare facilities per 10,000 people, the per capita disposable income of urban residents, the annual average temperature, and the annual precipitation. (4) The spatial–temporal evolution of the coupling and coordinated development of the APLE system is the result of the comprehensive effect of internal driving forces such as food security, the consumption level of rural residents, and the development level of urbanization construction, and external driving forces such as government public welfare and natural conditions. [ABSTRACT FROM AUTHOR]

Under the "Double Carbon" background, the development of green agricultural machinery is very fast. An important factor that determines the performance of electric farm machinery is the endurance capacity, which is directly related to the running path of farm machinery. The optimized driving path can reduce the operating loss and extend the mileage of agricultural machinery, then multi-node path planning helps to improve the working efficiency of electric tractors. Ant Colony Optimization (ACO) is often used to solve multi-node path planning problems. However, ACO has some problems, such as poor global search ability, few initial pheromones, poor convergence, and weak optimization ability, which is not conducive to obtaining the optimal path. This paper proposes a multi-node path planning algorithm based on Improved Whale Optimized ACO, named IWOA-ACO. The algorithm first introduces reverse learning strategy, nonlinear convergence factor, and adaptive inertia weight factor to improve the global and local convergence ability. Then, an appropriate evaluation function is designed to evaluate the solving process and obtain the best fitting parameters of ACO. Finally, the optimal objective function, fast convergence, and stable operation requirements are achieved through the best fitting parameters to obtain the global path optimization. The simulation results show that in flat environment, the length and energy consumption of IWOA-ACO planned path are the same as those of PSO-ACO, and are 0.61% less than those of WOA-ACO. In addition, in bump environment, the length and energy consumption of IWOA-ACO planned path are 1.91% and 4.32% less than those of PSO-ACO, and are 1.95% and 1.25% less than those of WOA-ACO. Therefore, it is helpful to improve the operating efficiency along with the endurance of electric tractors, which has practical application value. [ABSTRACT FROM AUTHOR]

In Sub-Saharan Africa, economic growth is essential for poverty reduction, and pro-poor growth is the renewed focus of today's political debate. The present paper adds to the literature on the growth–inequality relationship. It provides an in-depth analysis of the potential role of agriculture in promoting pro-poor growth in rural and urban areas compared with that of other activities. This aspect still lacks rigorous empirical support. Using the Nexus project SAMs by the International Food Policy Research Institute, this study identifies the level of 'keyness' of 36 activities (12 are agricultural) in nine Eastern, Western, and Central African countries using the inter-industry linkages analysis. Afterwards, it investigates the income distribution multipliers effects of activities growth across households classified in quantiles in rural and urban areas. Therefore, the paper adds to the literature, mainly focused on rural poverty and information on the growth effect on urban poverty, which is important in the context of rapid urbanization and the growing number of poor people in African cities. Apart from country-specific factors, the results confirm the strong integration of agriculture with the economy. The growth of key agricultural activities presents the most pronounced multiplicative effect on the income of rural households in the lowest quantiles. Poor urban households also benefit from their growth, but not to the same extent as rural households with an increase in the rural–urban income gap. [ABSTRACT FROM AUTHOR]

Green agriculture is the future of agricultural development. However, there has been little attention paid to the relationship between market-oriented reform of agricultural subsidies and green agricultural development. Based on the quasi-natural experiment of China's maize purchasing and storage policy reform (MPSR), this paper studied the impact of agricultural subsidy market-oriented reform on agricultural green development from the perspective of green total factor productivity using the difference-in-difference model. The results showed that the green total factor productivity (MGTFP) of maize in China from 2010 to 2020 presented an upward trend with an average annual growth rate of 0.70%, which mainly depended on the contribution of green technical progress in maize. MPSR could promote the improvement of MGTFP, but the result had a hysteresis effect. In addition, MPSR had a significant promoting effect on green technical change but had no significant impact on green technical efficiency. The policy implication of this paper is that developing countries should actively promote the market-oriented reform of agricultural subsidies to promote green agricultural development. [ABSTRACT FROM AUTHOR]

Groundwater resources serve as the primary source of water in the agro-pastoral ecotone of northern China, where scarcity of water resources constrains the development of agriculture and animal husbandry. As a typical rainfed agricultural area, the agro-pastoral ecotone in Inner Mongolia is entirely dependent on groundwater for agricultural irrigation. Due to the substantial groundwater consumption of irrigated farmland, groundwater levels have been progressively declining. To obtain a sustainable irrigation pattern that significantly conserves water, this study faces the challenge of unclear water transport relationships among water, soil, and crops, undefined water cycle mechanism in typical irrigation units, and water use efficiency, which was not assessed. Therefore, this paper, based on in situ experimental observations and daily meteorological data in 2022–2023, utilized the DSSAT model to explore the growth processes of potato, oat, alfalfa, and sunflower, the soil water dynamics, the water balance, and water use efficiency, analyzed over a typical irrigation area. The results indicated that the simulation accuracy of the DSSAT model was ARE < 10%, nRMSE/% < 10%, and R2 ≥ 0.85. The consumption of the soil moisture during the rapid growth stage for the potatoes, oats, alfalfa, and sunflower was 7–13% more than that during the other periods, and the yield was 67,170, 3345, 6529, and 4020 kg/ha, respectively. The soil evaporation of oat, potato, alfalfa, and sunflower accounted for 18–22%, 78–82%; 57–68%, and 32–43%, and transpiration accounted for 40–44%, 56–60%, 45–47%, and 53–55% of ETa (333.8 mm–369.2 mm, 375.2 mm–414.2 mm, 415.7 mm–453.7 mm, and 355.0 mm–385.6 mm), respectively. It was advised that irrigation water could be appropriately reduced to decrease ineffective water consumption. The water use efficiency and irrigation water use efficiency for potatoes was at the maximum amount, ranging from 16.22 to 16.62 kg/m3 and 8.61 to 10.81 kg/m3, respectively, followed by alfalfa, sunflowers, and oats. For the perspective of water productivity, it was recommended that potatoes could be extensively cultivated, alfalfa planted appropriately, and oats and sunflowers planted less. The findings of this study provided a theoretical basis for efficient water resource use in the agro-pastoral ecotone of Northern China. [ABSTRACT FROM AUTHOR]

Introduction: The implementation of cultivated land quality protection is fundamental for ensuring the sustainable use of land resources, and it is the inevitable choice for maintaining the balance of agricultural ecology and promoting the long-term healthy development of agriculture. Methods: Based on survey data from 927 grain family farms in 13 major grain-producing areas in China, this paper empirically tests the effects of participation in cooperatives on the cultivated land quality protection behavior of grain family farms by using a logit model, an ordered probit model and the propensity score matching method. Results: The results show that participation in cooperatives has a significant positive effect on the implementation of cultivated land quality protection behavior and the degree of cultivated land quality protection of grain family farms. A series of robustness tests reveals that the conclusion of the study does not change. Heterogeneity analysis reveals that the probability of implementing cultivated land quality protection behavior significantly increased, and the effect was greater for farms with the younger farmers, farmers of lower education level, farmers of non-party members, larger scale of operation, longer establishment years, larger labor force, or provincial demonstration. Discussion: On this basis, we should vigorously support and guide grain family farms to participate in cooperatives, give full play to the advantages of cooperatives, effectively encourage farms to implement cultivated land quality protection behavior, and promote sustainable agricultural development. [ABSTRACT FROM AUTHOR]

Agricultural development is crucial to feed the growing population. Most farmers tend to cultivate the crops which will give the more economical benefits besides checking the suitability of the crop according to the soil conditions. Use of technology in the agricultural sector leads the sustainable improvements in the agricultural production. Machine learning approach to suggest the suitable crop based on the soil parameters can help the farmers to cultivate the crops accordingly and can produce more yield. In this paper Random Forest Classifier is used to train the Machine Learning model on soil dataset using Python. Model performance is evaluated using confusion matrix and classification report having precision, recall and F1 score. Model accuracy achieved is 99% without parameter tuning. [ABSTRACT FROM AUTHOR]

Straw return is a crucial method for utilizing agricultural waste as a resource. Against the backdrop of increasing straw production in China, most scholars focus only on the behavioral decision of whether farmers choose to transfer land. However, few studies have touched on the specific content of the land transfer contract and its impact on farmers' behavior. This paper innovatively starts from the perspective of land transfer contracts to explore the impact of land transfer contracts on straw return in terms of standardization, stability, and profitability and to make theoretical contributions to the rational use of straw and the protection of arable land resources. Using data from the 2020 China Rural Revitalization Survey (CRRS) database, this study empirically analyzed the effects of different elements of land transfer contracts on straw returns to the field. The results show that: (1) Written transfer contracts are more effective than verbal contracts in encouraging farmers to adopt the straw return behavior. (2) Fixed-term contracts are more stable and can effectively promote farmers' adoption of straw return technology. (3) The remunerative transfer method is more profitable and can effectively encourage farmers to adopt straw return technology compared to the non-remunerative transfer method. (4) Farmers in mountainous areas or with smaller areas of farmland have a lower probability of adopting straw return technology. Therefore, the important role of remunerative, fixed-term, written land transfer contracts in the process of straw return should be emphasized, and the adoption rate of straw return should be increased through differentiated policy guidance and comprehensively promoting the sustainable development of agriculture. [ABSTRACT FROM AUTHOR]

Establishing a management information system that adapts to the continuous development of agricultural production management today, adopting advanced 5G technology and means, and comprehensively managing the entire agricultural production is an inevitable trend in the development of agricultural production management. In order to improve the effect of agricultural production informatization management, this paper combines 5G (fifth-generation) network technology to construct agricultural production and informatization management models. In view of the massive dynamic agricultural production management data, this paper studies the efficient multi-copy management strategy, which can consider the two aspects of load balancing and energy efficiency at the same time, so as to achieve efficient data access and energy efficiency. Moreover, this paper introduces a time series-based file access heat calculation model. In terms of determining the number of copies of files, this paper proposes a copy factor allocation algorithm centered on the ranking of file access popularity, and gives a characteristic function. Through cluster analysis, it can be seen that the agricultural production informatization management model based on 5G technology proposed in this paper can effectively improve the efficiency of agricultural information management. [ABSTRACT FROM AUTHOR]

Water is considered one of the vital natural resources and factors for performing short- and long-term agricultural practices on Earth. Meanwhile, globally, most of the available freshwater resources are utilized for irrigation purposes in agriculture. Currently, many world regions are facing extreme water shortage problems, which can worsen if not managed properly. In the literature, numerous methods and remedies are used to cope with the increasing global water crises. The use of precision irrigation water-saving systems (PISs) for efficient water management under climate change is one of them and is a highly recommended approach by researchers. It can mitigate the adverse effects of changing climate and help enhance water use efficiency, crop yield, and environmental footprints. Thus, the present study aimed to comprehensively examine and review PISs, focusing on their development, implementation, and positive impacts on sustainable water management. In addition, we searched the literature using different online search engines and reviewed and summarized the main results of the previously published papers on PISs. We discussed the traditional irrigation method and its modernization for enhancing water use efficiency, PIS monitoring and controlling, architecture, data sharing communication technologies, the role of artificial intelligence for irrigation water-saving, and the future prospects of the PIS. Based on the brief literature review, the present study concluded that the future of PISs seems bright, driven by the need for efficient irrigation water management systems, technological advancements, and increasing environmental awareness. As the water scarcity problem intensifies due to climate change and population growth, the PIS is poised to play a critical role in optimizing and modernizing water usage, increasing water use efficiency, and reducing environmental footprints, thus ensuring sustainable agriculture development. [ABSTRACT FROM AUTHOR]

Advancing the construction and application of new quality productive forces is an essential prerequisite for achieving high-quality agricultural development and expediting the establishment of agricultural powerhouses. This study aims to elucidate the internal mechanisms through which new quality productivity contributes to high-quality agricultural development and to explore practical pathways for enhancing agricultural quality through its promotion. Utilizing panel data spanning 2012 to 2021 from 30 provinces and municipalities in mainland China, the entropy method is employed to gauge levels of new quality productivity and high-quality agricultural development. Additionally, employing research methodologies including SYS-GMM and threshold effect models, this study empirically investigates how the advancement of new quality productivity influences high-quality agricultural development. Our research reveals the following key findings: (1) The development of new quality productive forces significantly enhances high-quality agricultural development, exhibiting a heterogeneous distribution pattern favoring the "eastern region > western region > central region" and "northern region > southern region". (2) New quality productive forces can bolster the level of high-quality agricultural development by fostering innovation, coordination, openness, and shared development within its subsystems. However, they may impede progress by inhibiting improvements in green development within the subsystems. (3) The results of the threshold effect test demonstrate that the promotion effect of the development of new quality productive forces on high-quality agricultural development escalates with the level of high-quality agricultural development. Specifically, as the level of high-quality agricultural development exceeds the first threshold value of 0.1502, the promotion effect becomes significant; crossing the second threshold value of 0.2010 further amplifies this effect. This paper's primary marginal contribution involves empirically analyzing the potential nonlinear effects of advancing new quality productivity in enhancing the level of high-quality agricultural development. This enriches empirical research on how new quality productivity fosters the development of high-quality agriculture. [ABSTRACT FROM AUTHOR]

Agriculture is crucial for the economy and individuals, and there is a pressing need to improve its quality, efficiency, and competitiveness in emerging countries. This study uses data from Chinese-listed companies to investigate the effect of trade credit on agricultural firms' total factor productivity. The results demonstrate that trade credit access and provision can increase agribusinesses' total factor productivity. Heterogeneity analysis reveals that access to business credit has a higher contribution to total factor productivity for agribusinesses in the primary sector, for firms in the versus maturity stage, and with low or medium supplier concentration. The provision of trade credit has a more pronounced positive impact on agribusinesses in the maturing stage and enterprises with low or medium customer concentration. This paper further validates the channels of action through which trade credit affects a firm's highquality development. This research makes a valuable contribution to enhancing the quality and productivity of China's agricultural sector. [ABSTRACT FROM AUTHOR]

In the climate-development interface, research for development gained a strong interest in climate-smart agriculture and sustainable forms of intensification. Moreover, the urgency to respond to climate change stimulates a strong and sometimes exclusive focus on mitigation, driven by research-based agricultural practices. In the livestock sector, this materialises in strategies to lower emissions from livestock, which centralises the adoption question: what can we do to stimulate the use of best practices by smallholder farmers? This paper flags the risk that this outlook may overlooksmallholder farmers' capacities to navigate sub-optimal conditions of drought or scarcity. The paper applies an alternative lens for understanding 'agriculture-as-performance' and highlights smallholder cattle owners' agency and resourcefulness. It aims to create a conceptual space to examine how adaptive capacities are grounded in the rhythms of agriculture under suboptimal conditions. Empirically, the study focuses on the cattle-feeding practices of five farming households evolving through seasons and lifetimes in a sedentary agricultural system in Kenya. Our frame identifies diverse affordances, conceptualised as opportunities for actions, emerging and disappearing in the immediate material environment, and we portray cattle feeding as a networked response anchored in practices of giving, sharing, and receiving. We use our insights into the dynamics and performance of entangled socio-technical practices to sketch the contours of an alternative pathway for agriculture for development. We argue in favour of a shift from an exclusive focus on the adoption of predefined optimal solutions to a diagnostic and catalytic approach integrating situated adaptive performances through which farming households respond to action opportunities. [ABSTRACT FROM AUTHOR]

This paper identified the intangible aspects (IA) that generate impacts in companies of the agricultural sector in the different stages of the companies life cycle. This paper is based on a systematic review methodology to identify intangibles in the agricultural sector. Studies on the life cycle of companies were analyzed to classify the impact of intangible aspects according to the reality of companies. Identify the intangible aspects that impact the agricultural sector through a review of the scientific literature. How intangible aspects affect each stage of the life cycle of companies in the sector shows that they have a different impact depending on the period in which the company is located. Although, much of the previous literature has suggested that intangible aspects have positive effects on a variety of performance variables, there are no scientific studies that specifically address the importance of these intangible aspects in the life cycle of companies in the agricultural sector. [ABSTRACT FROM AUTHOR]

Agricultural development is one of the most essential needs worldwide. In Norway, the primary foundation of grain production is based on geological and biological features. Existing research is limited to regional-scale yield predictions using artificial intelligence (AI) models, which provide a holistic overview of crop growth. In this paper, the authors propose detecting several field-scale crop types and use this analysis to predict yield production early in the growing season. In this study, the authors utilise a multi-temporal satellite image, meteorological, geographical, and grain production data corpus. The authors extract relevant vegetation indices from satellite images. Furthermore, the authors use field-area-specific features to build a field-based crop type classification model. The proposed model, consisting of a time-distributed network and a gated recurrent unit, can efficiently classify crop types with an accuracy of 70%. In addition, the authors justified that the attention-based multiple-instance learning models could learn semi-labelled agricultural data, and thus, allow realistic early in-season predictions for farmers. [ABSTRACT FROM AUTHOR]